PID神经元网络在水稻秧棚控制系统中的应用研究

育秧对水稻的生产起着至关重要的作用,为水稻秧苗提供适宜生长的环境条件就成为水稻生产中极为重要的一环。水稻育秧棚控制系统具有多变量、大惯性、非线性、强耦合及时滞等特点,采用传统PID控制不能获得满意的控制效果。为此,本文将常规的PID控制和BP神经元网络控制相结合,设计了水稻育秧棚温、湿度解耦自动控制系统,并利用仿真软件(MatLab/SIMULINK)对秧棚内PID神经元网络控制系统进行了仿真及分析。结果表明:基于PID神经元网络控制与传统PID控制相比,响应速度快、超调量小、无静差,大大提高了秧棚内控制系统的性能,达到了预期的控制效果。

Application of PID Neural Network in Rice Seedling Control System

The control system of rice seedling raising has many characteristics such as multivariable,large inertia,nonlinearity,strong coupling and time delay.The traditional PID control can not get satisfactory control effect.In this paper,the conventional PID control and BP neural network control are combined,The control system of rice seedling transplanting temperature and humidity was designed and the control system was simulated by MATLAB/SIMULINK software.Results show that compared with the traditional PID control based on PID neural network control,response speed,less overshoot and astatic,greatly improving the seedling relative performance of the control system,and achieve the expected control effect,to provide theoretical guidance for expanding the output of rice and promoting agricultural production automation and technology.